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We compare different neural network architectures for Machine Learning (ML) algorithms designed to identify the neutrino interaction vertex position in the MINERvA detector. The architectures developed and optimized by hand are compared with the architectures developed in an automated way using the package "Multi-node Evolutionary Neural Networks for Deep Learning" (MENNDL), developed at Oak Ridge National Laboratory (ORNL). The two architectures resulted in a similar performance which suggests that the systematics associated with the optimized network architecture are small. Furthermore, we find that while the domain expert hand-tuned network was the best performer, the differences were negligible and the auto-generated networks performed well. There is always a trade-off between human, and computer resources for network optimization and this work suggests that automated optimization, assuming resources are available, provides a compelling way to save significant expert time.

Inverse muon decay, $\nu_\mu e^-\to\mu^-\nu_e$, is a reaction whose cross-section can be predicted with very small uncertainties. It has a neutrino energy threshold of $\approx 11$ GeV and can be used to constrain the high-energy part of the flux in the NuMI neutrino beam. This reaction is the dominant source of events which only contain high-energy muons nearly parallel to the direction of the neutrino beam. We have isolated a sample of hundreds of such events in neutrino and anti-neutrino enhanced beams, and have constrained the predicted high-energy flux., Comment: 9 pages, 8 figures, submitted to Physical Review D. Minor corrections and clarifications

With the advance of particle accelerator and detector technologies, the neutrino physics landscape is rapidly expanding. As neutrino oscillation experiments enter the intensity and precision frontiers, neutrino-nucleus interaction measurements are providing crucial input. MINERvA is an experiment at Fermilab dedicated to the study of neutrino-nucleus interactions in the regime of incident neutrino energies from one to few GeV. The experiment recorded neutrino and antineutrino scattering data with the NuMI beamline from 2009 to 2019 using the Low-Energy and Medium-Energy beams that peak at 3 GeV and 6 GeV, respectively. This article reviews the broad spectrum of interesting nuclear and particle physics that MINERvA investigations have illuminated. The newfound, detailed knowledge of neutrino interactions with nuclear targets thereby obtained is proving essential to continued progress in the neutrino physics sector., 22 pages, 17 figures. Accepted as invited contribution to EPJ special issue "Neutrino Interactions in the Intermediate and High Energy Region. Guest editors: Mohammad Sajjad Athar and Shri Krishna Singh"